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  <h1>Source code for torch_tensorrt.ts._compile_spec</h1><div class="highlight"><pre>
<span></span><span class="kn">from</span> <span class="nn">typing</span> <span class="kn">import</span> <span class="n">List</span><span class="p">,</span> <span class="n">Dict</span><span class="p">,</span> <span class="n">Any</span><span class="p">,</span> <span class="n">Set</span>
<span class="kn">import</span> <span class="nn">torch</span>
<span class="kn">from</span> <span class="nn">torch_tensorrt</span> <span class="kn">import</span> <span class="n">_C</span>
<span class="kn">import</span> <span class="nn">torch_tensorrt._C.ts</span> <span class="k">as</span> <span class="nn">_ts_C</span>
<span class="kn">from</span> <span class="nn">torch_tensorrt</span> <span class="kn">import</span> <span class="n">_enums</span>
<span class="kn">from</span> <span class="nn">torch_tensorrt._Input</span> <span class="kn">import</span> <span class="n">Input</span>
<span class="kn">from</span> <span class="nn">torch_tensorrt._Device</span> <span class="kn">import</span> <span class="n">Device</span>
<span class="kn">from</span> <span class="nn">torch_tensorrt.logging</span> <span class="kn">import</span> <span class="n">Level</span><span class="p">,</span> <span class="n">log</span>
<span class="kn">from</span> <span class="nn">typing</span> <span class="kn">import</span> <span class="n">Tuple</span><span class="p">,</span> <span class="n">List</span><span class="p">,</span> <span class="n">Dict</span>
<span class="kn">import</span> <span class="nn">warnings</span>
<span class="kn">from</span> <span class="nn">copy</span> <span class="kn">import</span> <span class="n">deepcopy</span>


<span class="k">def</span> <span class="nf">_internal_input_to_torch_class_input</span><span class="p">(</span><span class="n">i</span><span class="p">:</span> <span class="n">_C</span><span class="o">.</span><span class="n">Input</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">torch</span><span class="o">.</span><span class="n">classes</span><span class="o">.</span><span class="n">tensorrt</span><span class="o">.</span><span class="n">_Input</span><span class="p">:</span>
    <span class="n">clone</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">classes</span><span class="o">.</span><span class="n">tensorrt</span><span class="o">.</span><span class="n">_Input</span><span class="p">()</span>
    <span class="n">clone</span><span class="o">.</span><span class="n">_set_min</span><span class="p">(</span><span class="n">i</span><span class="o">.</span><span class="n">min</span><span class="p">)</span>
    <span class="n">clone</span><span class="o">.</span><span class="n">_set_opt</span><span class="p">(</span><span class="n">i</span><span class="o">.</span><span class="n">opt</span><span class="p">)</span>
    <span class="n">clone</span><span class="o">.</span><span class="n">_set_max</span><span class="p">(</span><span class="n">i</span><span class="o">.</span><span class="n">max</span><span class="p">)</span>
    <span class="n">clone</span><span class="o">.</span><span class="n">_set_dtype</span><span class="p">(</span><span class="n">i</span><span class="o">.</span><span class="n">dtype</span><span class="p">)</span>
    <span class="n">clone</span><span class="o">.</span><span class="n">_set_format</span><span class="p">(</span><span class="n">i</span><span class="o">.</span><span class="n">format</span><span class="p">)</span>
    <span class="n">clone</span><span class="o">.</span><span class="n">_set_input_is_dynamic</span><span class="p">(</span><span class="n">i</span><span class="o">.</span><span class="n">input_is_dynamic</span><span class="p">)</span>
    <span class="n">clone</span><span class="o">.</span><span class="n">_set_explicit_set_dtype</span><span class="p">(</span><span class="n">i</span><span class="o">.</span><span class="n">_explicit_set_dtype</span><span class="p">)</span>
    <span class="k">return</span> <span class="n">clone</span>


<span class="k">def</span> <span class="nf">_supported_input_size_type</span><span class="p">(</span><span class="n">input_size</span><span class="p">:</span> <span class="n">Any</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">bool</span><span class="p">:</span>
    <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">input_size</span><span class="p">,</span> <span class="n">torch</span><span class="o">.</span><span class="n">Size</span><span class="p">):</span>
        <span class="k">return</span> <span class="kc">True</span>
    <span class="k">elif</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">input_size</span><span class="p">,</span> <span class="nb">tuple</span><span class="p">):</span>
        <span class="k">return</span> <span class="kc">True</span>
    <span class="k">elif</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">input_size</span><span class="p">,</span> <span class="nb">list</span><span class="p">):</span>
        <span class="k">return</span> <span class="kc">True</span>
    <span class="k">else</span><span class="p">:</span>
        <span class="k">raise</span> <span class="ne">TypeError</span><span class="p">(</span>
            <span class="s2">&quot;Input sizes for inputs are required to be a List, tuple or torch.Size or a Dict of three sizes (min, opt, max), found type: &quot;</span>
            <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="nb">type</span><span class="p">(</span><span class="n">input_size</span><span class="p">))</span>
        <span class="p">)</span>


<span class="k">def</span> <span class="nf">_parse_input_ranges</span><span class="p">(</span><span class="n">input_sizes</span><span class="p">:</span> <span class="n">List</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">List</span><span class="p">:</span>

    <span class="k">if</span> <span class="nb">any</span><span class="p">(</span>
        <span class="ow">not</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">i</span><span class="p">,</span> <span class="nb">dict</span><span class="p">)</span> <span class="ow">and</span> <span class="ow">not</span> <span class="n">_supported_input_size_type</span><span class="p">(</span><span class="n">i</span><span class="p">)</span>
        <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">input_sizes</span>
    <span class="p">):</span>
        <span class="k">raise</span> <span class="ne">KeyError</span><span class="p">(</span>
            <span class="s2">&quot;An input size must either be a static size or a range of three sizes (min, opt, max) as Dict&quot;</span>
        <span class="p">)</span>

    <span class="n">parsed_input_sizes</span> <span class="o">=</span> <span class="p">[]</span>
    <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">input_sizes</span><span class="p">:</span>
        <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">i</span><span class="p">,</span> <span class="nb">dict</span><span class="p">):</span>
            <span class="k">if</span> <span class="nb">all</span><span class="p">(</span><span class="n">k</span> <span class="ow">in</span> <span class="n">i</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="p">[</span><span class="s2">&quot;min&quot;</span><span class="p">,</span> <span class="s2">&quot;opt&quot;</span><span class="p">,</span> <span class="s2">&quot;min&quot;</span><span class="p">]):</span>
                <span class="n">parsed_input_sizes</span><span class="o">.</span><span class="n">append</span><span class="p">(</span>
                    <span class="n">Input</span><span class="p">(</span>
                        <span class="n">min_shape</span><span class="o">=</span><span class="n">i</span><span class="p">[</span><span class="s2">&quot;min&quot;</span><span class="p">],</span> <span class="n">opt_shape</span><span class="o">=</span><span class="n">i</span><span class="p">[</span><span class="s2">&quot;opt&quot;</span><span class="p">],</span> <span class="n">max_shape</span><span class="o">=</span><span class="n">i</span><span class="p">[</span><span class="s2">&quot;max&quot;</span><span class="p">]</span>
                    <span class="p">)</span><span class="o">.</span><span class="n">_to_internal</span><span class="p">()</span>
                <span class="p">)</span>

            <span class="k">elif</span> <span class="s2">&quot;opt&quot;</span> <span class="ow">in</span> <span class="n">i</span><span class="p">:</span>
                <span class="n">parsed_input_sizes</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">Input</span><span class="p">(</span><span class="n">shape</span><span class="o">=</span><span class="n">i</span><span class="p">[</span><span class="s2">&quot;opt&quot;</span><span class="p">])</span><span class="o">.</span><span class="n">_to_internal</span><span class="p">())</span>

            <span class="k">else</span><span class="p">:</span>
                <span class="k">raise</span> <span class="ne">KeyError</span><span class="p">(</span>
                    <span class="s2">&quot;An input size must either be a static size or a range of three sizes (min, opt, max) as Dict&quot;</span>
                <span class="p">)</span>

        <span class="k">elif</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">i</span><span class="p">,</span> <span class="nb">list</span><span class="p">):</span>
            <span class="n">parsed_input_sizes</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">Input</span><span class="p">(</span><span class="n">shape</span><span class="o">=</span><span class="n">i</span><span class="p">)</span><span class="o">.</span><span class="n">_to_internal</span><span class="p">())</span>

        <span class="k">elif</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">i</span><span class="p">,</span> <span class="nb">tuple</span><span class="p">):</span>
            <span class="n">parsed_input_sizes</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">Input</span><span class="p">(</span><span class="n">shape</span><span class="o">=</span><span class="n">i</span><span class="p">)</span><span class="o">.</span><span class="n">_to_internal</span><span class="p">())</span>

        <span class="k">elif</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">i</span><span class="p">,</span> <span class="n">torch</span><span class="o">.</span><span class="n">Size</span><span class="p">):</span>
            <span class="n">parsed_input_sizes</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">Input</span><span class="p">(</span><span class="n">shape</span><span class="o">=</span><span class="n">i</span><span class="p">)</span><span class="o">.</span><span class="n">_to_internal</span><span class="p">())</span>

    <span class="k">return</span> <span class="n">parsed_input_sizes</span>


<span class="k">def</span> <span class="nf">_parse_op_precision</span><span class="p">(</span><span class="n">precision</span><span class="p">:</span> <span class="n">Any</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">_enums</span><span class="o">.</span><span class="n">dtype</span><span class="p">:</span>
    <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">precision</span><span class="p">,</span> <span class="n">torch</span><span class="o">.</span><span class="n">dtype</span><span class="p">):</span>
        <span class="k">if</span> <span class="n">precision</span> <span class="o">==</span> <span class="n">torch</span><span class="o">.</span><span class="n">int8</span><span class="p">:</span>
            <span class="k">return</span> <span class="n">_enums</span><span class="o">.</span><span class="n">dtype</span><span class="o">.</span><span class="n">int8</span>
        <span class="k">elif</span> <span class="n">precision</span> <span class="o">==</span> <span class="n">torch</span><span class="o">.</span><span class="n">half</span><span class="p">:</span>
            <span class="k">return</span> <span class="n">_enums</span><span class="o">.</span><span class="n">dtype</span><span class="o">.</span><span class="n">half</span>
        <span class="k">elif</span> <span class="n">precision</span> <span class="o">==</span> <span class="n">torch</span><span class="o">.</span><span class="n">float</span><span class="p">:</span>
            <span class="k">return</span> <span class="n">_enums</span><span class="o">.</span><span class="n">dtype</span><span class="o">.</span><span class="n">float</span>
        <span class="k">else</span><span class="p">:</span>
            <span class="k">raise</span> <span class="ne">TypeError</span><span class="p">(</span>
                <span class="s2">&quot;Provided an unsupported dtype as operating precision (support: int8, half, float), got: &quot;</span>
                <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">precision</span><span class="p">)</span>
            <span class="p">)</span>

    <span class="k">elif</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">precision</span><span class="p">,</span> <span class="n">_enums</span><span class="o">.</span><span class="n">dtype</span><span class="p">):</span>
        <span class="k">return</span> <span class="n">precision</span>

    <span class="k">else</span><span class="p">:</span>
        <span class="k">raise</span> <span class="ne">TypeError</span><span class="p">(</span>
            <span class="s2">&quot;Op precision type needs to be specified with a torch.dtype or a torch_tensorrt.dtype, got: &quot;</span>
            <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="nb">type</span><span class="p">(</span><span class="n">precision</span><span class="p">))</span>
        <span class="p">)</span>


<span class="k">def</span> <span class="nf">_parse_enabled_precisions</span><span class="p">(</span><span class="n">precisions</span><span class="p">:</span> <span class="n">Any</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Set</span><span class="p">:</span>
    <span class="n">parsed_precisions</span> <span class="o">=</span> <span class="nb">set</span><span class="p">()</span>
    <span class="k">if</span> <span class="nb">any</span><span class="p">([</span><span class="nb">isinstance</span><span class="p">(</span><span class="n">precisions</span><span class="p">,</span> <span class="nb">type</span><span class="p">)</span> <span class="k">for</span> <span class="nb">type</span> <span class="ow">in</span> <span class="p">[</span><span class="nb">list</span><span class="p">,</span> <span class="nb">tuple</span><span class="p">,</span> <span class="nb">set</span><span class="p">]]):</span>
        <span class="k">for</span> <span class="n">p</span> <span class="ow">in</span> <span class="n">precisions</span><span class="p">:</span>
            <span class="n">parsed_precisions</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="n">_parse_op_precision</span><span class="p">(</span><span class="n">p</span><span class="p">))</span>
    <span class="k">else</span><span class="p">:</span>
        <span class="n">parsed_precisions</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="n">_parse_op_precision</span><span class="p">(</span><span class="n">precisions</span><span class="p">))</span>
    <span class="k">return</span> <span class="n">parsed_precisions</span>


<span class="k">def</span> <span class="nf">_parse_device_type</span><span class="p">(</span><span class="n">device</span><span class="p">:</span> <span class="n">Any</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">_enums</span><span class="o">.</span><span class="n">DeviceType</span><span class="p">:</span>
    <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">device</span><span class="p">,</span> <span class="n">torch</span><span class="o">.</span><span class="n">device</span><span class="p">):</span>
        <span class="k">if</span> <span class="n">device</span><span class="o">.</span><span class="n">type</span> <span class="o">==</span> <span class="s2">&quot;cuda&quot;</span><span class="p">:</span>
            <span class="k">return</span> <span class="n">_enums</span><span class="o">.</span><span class="n">DeviceType</span><span class="o">.</span><span class="n">gpu</span>
        <span class="k">else</span><span class="p">:</span>
            <span class="ne">ValueError</span><span class="p">(</span>
                <span class="s2">&quot;Got a device type other than GPU or DLA (type: &quot;</span>
                <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">device</span><span class="o">.</span><span class="n">type</span><span class="p">)</span>
                <span class="o">+</span> <span class="s2">&quot;)&quot;</span>
            <span class="p">)</span>
    <span class="k">elif</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">device</span><span class="p">,</span> <span class="n">_enums</span><span class="o">.</span><span class="n">DeviceType</span><span class="p">):</span>
        <span class="k">return</span> <span class="n">device</span>
    <span class="k">elif</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">device</span><span class="p">,</span> <span class="nb">str</span><span class="p">):</span>
        <span class="k">if</span> <span class="n">device</span> <span class="o">==</span> <span class="s2">&quot;gpu&quot;</span> <span class="ow">or</span> <span class="n">device</span> <span class="o">==</span> <span class="s2">&quot;GPU&quot;</span><span class="p">:</span>
            <span class="k">return</span> <span class="n">_enums</span><span class="o">.</span><span class="n">DeviceType</span><span class="o">.</span><span class="n">gpu</span>
        <span class="k">elif</span> <span class="n">device</span> <span class="o">==</span> <span class="s2">&quot;dla&quot;</span> <span class="ow">or</span> <span class="n">device</span> <span class="o">==</span> <span class="s2">&quot;DLA&quot;</span><span class="p">:</span>
            <span class="k">return</span> <span class="n">_enums</span><span class="o">.</span><span class="n">DeviceType</span><span class="o">.</span><span class="n">dla</span>
        <span class="k">else</span><span class="p">:</span>
            <span class="ne">ValueError</span><span class="p">(</span>
                <span class="s2">&quot;Got a device type other than GPU or DLA (type: &quot;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">device</span><span class="p">)</span> <span class="o">+</span> <span class="s2">&quot;)&quot;</span>
            <span class="p">)</span>
    <span class="k">else</span><span class="p">:</span>
        <span class="k">raise</span> <span class="ne">TypeError</span><span class="p">(</span>
            <span class="s2">&quot;Device specification must be of type torch.device, string or torch_tensorrt.DeviceType, but got: &quot;</span>
            <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="nb">type</span><span class="p">(</span><span class="n">device</span><span class="p">))</span>
        <span class="p">)</span>


<span class="k">def</span> <span class="nf">_parse_device</span><span class="p">(</span><span class="n">device_info</span><span class="p">:</span> <span class="n">Any</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">_C</span><span class="o">.</span><span class="n">Device</span><span class="p">:</span>
    <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">device_info</span><span class="p">,</span> <span class="nb">dict</span><span class="p">):</span>
        <span class="n">info</span> <span class="o">=</span> <span class="n">_C</span><span class="o">.</span><span class="n">Device</span><span class="p">()</span>
        <span class="k">if</span> <span class="s2">&quot;device_type&quot;</span> <span class="ow">not</span> <span class="ow">in</span> <span class="n">device_info</span><span class="p">:</span>
            <span class="k">raise</span> <span class="ne">KeyError</span><span class="p">(</span><span class="s2">&quot;Device type is required parameter&quot;</span><span class="p">)</span>
        <span class="k">else</span><span class="p">:</span>
            <span class="k">assert</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">device_info</span><span class="p">[</span><span class="s2">&quot;device_type&quot;</span><span class="p">],</span> <span class="n">_enums</span><span class="o">.</span><span class="n">DeviceType</span><span class="p">)</span>
            <span class="n">info</span><span class="o">.</span><span class="n">device_type</span> <span class="o">=</span> <span class="n">_parse_device_type</span><span class="p">(</span><span class="n">device_info</span><span class="p">[</span><span class="s2">&quot;device_type&quot;</span><span class="p">])</span>

        <span class="k">if</span> <span class="s2">&quot;gpu_id&quot;</span> <span class="ow">in</span> <span class="n">device_info</span><span class="p">:</span>
            <span class="k">assert</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">device_info</span><span class="p">[</span><span class="s2">&quot;gpu_id&quot;</span><span class="p">],</span> <span class="nb">int</span><span class="p">)</span>
            <span class="n">info</span><span class="o">.</span><span class="n">gpu_id</span> <span class="o">=</span> <span class="n">device_info</span><span class="p">[</span><span class="s2">&quot;gpu_id&quot;</span><span class="p">]</span>

        <span class="k">if</span> <span class="s2">&quot;dla_core&quot;</span> <span class="ow">in</span> <span class="n">device_info</span><span class="p">:</span>
            <span class="k">assert</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">device_info</span><span class="p">[</span><span class="s2">&quot;dla_core&quot;</span><span class="p">],</span> <span class="nb">int</span><span class="p">)</span>
            <span class="n">info</span><span class="o">.</span><span class="n">dla_core</span> <span class="o">=</span> <span class="n">device_info</span><span class="p">[</span><span class="s2">&quot;dla_core&quot;</span><span class="p">]</span>

        <span class="k">if</span> <span class="s2">&quot;allow_gpu_fallback&quot;</span> <span class="ow">in</span> <span class="n">device_info</span><span class="p">:</span>
            <span class="k">assert</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">device_info</span><span class="p">[</span><span class="s2">&quot;allow_gpu_fallback&quot;</span><span class="p">],</span> <span class="nb">bool</span><span class="p">)</span>
            <span class="n">info</span><span class="o">.</span><span class="n">allow_gpu_fallback</span> <span class="o">=</span> <span class="n">device_info</span><span class="p">[</span><span class="s2">&quot;allow_gpu_fallback&quot;</span><span class="p">]</span>

        <span class="k">return</span> <span class="n">info</span>
    <span class="k">elif</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">device_info</span><span class="p">,</span> <span class="n">Device</span><span class="p">):</span>
        <span class="k">return</span> <span class="n">device_info</span><span class="o">.</span><span class="n">_to_internal</span><span class="p">()</span>
    <span class="k">elif</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">device_info</span><span class="p">,</span> <span class="n">torch</span><span class="o">.</span><span class="n">device</span><span class="p">):</span>
        <span class="k">return</span> <span class="p">(</span><span class="n">Device</span><span class="o">.</span><span class="n">_from_torch_device</span><span class="p">(</span><span class="n">device_info</span><span class="p">))</span><span class="o">.</span><span class="n">_to_internal</span><span class="p">()</span>
    <span class="k">else</span><span class="p">:</span>
        <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span>
            <span class="s2">&quot;Unsupported data for device specification. Expected either a dict, torch_tensorrt.Device or torch.Device&quot;</span>
        <span class="p">)</span>


<span class="k">def</span> <span class="nf">_parse_torch_fallback</span><span class="p">(</span><span class="n">fallback_info</span><span class="p">:</span> <span class="n">Dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">Any</span><span class="p">])</span> <span class="o">-&gt;</span> <span class="n">_ts_C</span><span class="o">.</span><span class="n">TorchFallback</span><span class="p">:</span>
    <span class="n">info</span> <span class="o">=</span> <span class="n">_ts_C</span><span class="o">.</span><span class="n">TorchFallback</span><span class="p">()</span>
    <span class="k">if</span> <span class="s2">&quot;enabled&quot;</span> <span class="ow">not</span> <span class="ow">in</span> <span class="n">fallback_info</span><span class="p">:</span>
        <span class="k">raise</span> <span class="ne">KeyError</span><span class="p">(</span><span class="s2">&quot;Enabled is required parameter&quot;</span><span class="p">)</span>
    <span class="k">else</span><span class="p">:</span>
        <span class="k">assert</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">fallback_info</span><span class="p">[</span><span class="s2">&quot;enabled&quot;</span><span class="p">],</span> <span class="nb">bool</span><span class="p">)</span>
        <span class="n">info</span><span class="o">.</span><span class="n">enabled</span> <span class="o">=</span> <span class="n">fallback_info</span><span class="p">[</span><span class="s2">&quot;enabled&quot;</span><span class="p">]</span>
    <span class="k">if</span> <span class="s2">&quot;min_block_size&quot;</span> <span class="ow">in</span> <span class="n">fallback_info</span><span class="p">:</span>
        <span class="k">assert</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">fallback_info</span><span class="p">[</span><span class="s2">&quot;min_block_size&quot;</span><span class="p">],</span> <span class="nb">int</span><span class="p">)</span>
        <span class="n">info</span><span class="o">.</span><span class="n">min_block_size</span> <span class="o">=</span> <span class="n">fallback_info</span><span class="p">[</span><span class="s2">&quot;min_block_size&quot;</span><span class="p">]</span>

    <span class="k">if</span> <span class="s2">&quot;forced_fallback_ops&quot;</span> <span class="ow">in</span> <span class="n">fallback_info</span><span class="p">:</span>
        <span class="k">assert</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">fallback_info</span><span class="p">[</span><span class="s2">&quot;forced_fallback_ops&quot;</span><span class="p">],</span> <span class="nb">list</span><span class="p">)</span>
        <span class="n">info</span><span class="o">.</span><span class="n">forced_fallback_operators</span> <span class="o">=</span> <span class="n">fallback_info</span><span class="p">[</span><span class="s2">&quot;forced_fallback_ops&quot;</span><span class="p">]</span>

    <span class="k">if</span> <span class="s2">&quot;forced_fallback_modules&quot;</span> <span class="ow">in</span> <span class="n">fallback_info</span><span class="p">:</span>
        <span class="k">assert</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">fallback_info</span><span class="p">[</span><span class="s2">&quot;forced_fallback_modules&quot;</span><span class="p">],</span> <span class="nb">list</span><span class="p">)</span>
        <span class="n">info</span><span class="o">.</span><span class="n">forced_fallback_modules</span> <span class="o">=</span> <span class="n">fallback_info</span><span class="p">[</span><span class="s2">&quot;forced_fallback_modules&quot;</span><span class="p">]</span>

    <span class="k">return</span> <span class="n">info</span>


<span class="k">def</span> <span class="nf">_parse_input_signature</span><span class="p">(</span><span class="n">input_signature</span><span class="p">:</span> <span class="n">Any</span><span class="p">):</span>
    <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">input_signature</span><span class="p">,</span> <span class="nb">tuple</span><span class="p">):</span>
        <span class="n">input_list</span> <span class="o">=</span> <span class="p">[]</span>
        <span class="k">for</span> <span class="n">item</span> <span class="ow">in</span> <span class="n">input_signature</span><span class="p">:</span>
            <span class="nb">input</span> <span class="o">=</span> <span class="n">_parse_input_signature</span><span class="p">(</span><span class="n">item</span><span class="p">)</span>
            <span class="n">input_list</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="nb">input</span><span class="p">)</span>
        <span class="k">return</span> <span class="nb">tuple</span><span class="p">(</span><span class="n">input_list</span><span class="p">)</span>
    <span class="k">elif</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">input_signature</span><span class="p">,</span> <span class="nb">list</span><span class="p">):</span>
        <span class="n">input_list</span> <span class="o">=</span> <span class="p">[]</span>
        <span class="k">for</span> <span class="n">item</span> <span class="ow">in</span> <span class="n">input_signature</span><span class="p">:</span>
            <span class="nb">input</span> <span class="o">=</span> <span class="n">_parse_input_signature</span><span class="p">(</span><span class="n">item</span><span class="p">)</span>
            <span class="n">input_list</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="nb">input</span><span class="p">)</span>
        <span class="k">return</span> <span class="n">input_list</span>
    <span class="k">elif</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">input_signature</span><span class="p">,</span> <span class="n">Input</span><span class="p">)</span> <span class="ow">or</span> <span class="nb">isinstance</span><span class="p">(</span>
        <span class="n">input_signature</span><span class="p">,</span> <span class="n">torch</span><span class="o">.</span><span class="n">Tensor</span>
    <span class="p">):</span>
        <span class="n">i</span> <span class="o">=</span> <span class="p">(</span>
            <span class="n">Input</span><span class="o">.</span><span class="n">_from_tensor</span><span class="p">(</span><span class="n">input_signature</span><span class="p">)</span>
            <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">input_signature</span><span class="p">,</span> <span class="n">torch</span><span class="o">.</span><span class="n">Tensor</span><span class="p">)</span>
            <span class="k">else</span> <span class="n">input_signature</span>
        <span class="p">)</span>
        <span class="n">clone</span> <span class="o">=</span> <span class="n">_internal_input_to_torch_class_input</span><span class="p">(</span><span class="n">i</span><span class="o">.</span><span class="n">_to_internal</span><span class="p">())</span>
        <span class="k">return</span> <span class="n">clone</span>
    <span class="k">else</span><span class="p">:</span>
        <span class="k">raise</span> <span class="ne">KeyError</span><span class="p">(</span>
            <span class="s2">&quot;Input signature contains an unsupported type </span><span class="si">{}</span><span class="s2">&quot;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span>
                <span class="nb">type</span><span class="p">(</span><span class="n">input_signature</span><span class="p">)</span>
            <span class="p">)</span>
        <span class="p">)</span>


<span class="k">def</span> <span class="nf">_parse_compile_spec</span><span class="p">(</span><span class="n">compile_spec_</span><span class="p">:</span> <span class="n">Dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">Any</span><span class="p">])</span> <span class="o">-&gt;</span> <span class="n">_ts_C</span><span class="o">.</span><span class="n">CompileSpec</span><span class="p">:</span>
    <span class="c1"># TODO: Remove deep copy once collections does not need partial compilation</span>
    <span class="n">compile_spec</span> <span class="o">=</span> <span class="n">deepcopy</span><span class="p">(</span><span class="n">compile_spec_</span><span class="p">)</span>
    <span class="n">info</span> <span class="o">=</span> <span class="n">_ts_C</span><span class="o">.</span><span class="n">CompileSpec</span><span class="p">()</span>

    <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">compile_spec</span><span class="p">[</span><span class="s2">&quot;inputs&quot;</span><span class="p">])</span> <span class="o">&gt;</span> <span class="mi">0</span><span class="p">:</span>
        <span class="k">if</span> <span class="ow">not</span> <span class="nb">all</span><span class="p">(</span>
            <span class="p">[</span>
                <span class="nb">isinstance</span><span class="p">(</span><span class="n">i</span><span class="p">,</span> <span class="n">torch</span><span class="o">.</span><span class="n">Tensor</span><span class="p">)</span> <span class="ow">or</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">i</span><span class="p">,</span> <span class="n">Input</span><span class="p">)</span>
                <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">compile_spec</span><span class="p">[</span><span class="s2">&quot;inputs&quot;</span><span class="p">]</span>
            <span class="p">]</span>
        <span class="p">):</span>
            <span class="k">raise</span> <span class="ne">KeyError</span><span class="p">(</span>
                <span class="s2">&quot;Input specs should be either torch_tensorrt.Input or torch.Tensor, found types: </span><span class="si">{}</span><span class="s2">&quot;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span>
                    <span class="p">[</span><span class="nb">type</span><span class="p">(</span><span class="n">i</span><span class="p">)</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">compile_spec</span><span class="p">[</span><span class="s2">&quot;inputs&quot;</span><span class="p">]]</span>
                <span class="p">)</span>
            <span class="p">)</span>

        <span class="n">inputs</span> <span class="o">=</span> <span class="p">[</span>
            <span class="n">Input</span><span class="o">.</span><span class="n">_from_tensor</span><span class="p">(</span><span class="n">i</span><span class="p">)</span> <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">i</span><span class="p">,</span> <span class="n">torch</span><span class="o">.</span><span class="n">Tensor</span><span class="p">)</span> <span class="k">else</span> <span class="n">i</span>
            <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">compile_spec</span><span class="p">[</span><span class="s2">&quot;inputs&quot;</span><span class="p">]</span>
        <span class="p">]</span>
        <span class="n">info</span><span class="o">.</span><span class="n">inputs</span> <span class="o">=</span> <span class="p">[</span><span class="n">i</span><span class="o">.</span><span class="n">_to_internal</span><span class="p">()</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">inputs</span><span class="p">]</span>

    <span class="k">elif</span> <span class="n">compile_spec</span><span class="p">[</span><span class="s2">&quot;input_signature&quot;</span><span class="p">]</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
        <span class="n">log</span><span class="p">(</span>
            <span class="n">Level</span><span class="o">.</span><span class="n">Warning</span><span class="p">,</span>
            <span class="s2">&quot;Input signature parsing is an experimental feature, behavior and APIs may change&quot;</span><span class="p">,</span>
        <span class="p">)</span>
        <span class="n">signature</span> <span class="o">=</span> <span class="n">_parse_input_signature</span><span class="p">(</span><span class="n">compile_spec</span><span class="p">[</span><span class="s2">&quot;input_signature&quot;</span><span class="p">])</span>
        <span class="n">info</span><span class="o">.</span><span class="n">input_signature</span> <span class="o">=</span> <span class="n">_C</span><span class="o">.</span><span class="n">InputSignature</span><span class="p">(</span><span class="n">signature</span><span class="p">)</span>  <span class="c1"># py_object</span>

        <span class="k">if</span> <span class="ow">not</span> <span class="n">compile_spec</span><span class="p">[</span><span class="s2">&quot;torch_fallback&quot;</span><span class="p">][</span><span class="s2">&quot;enabled&quot;</span><span class="p">]:</span>
            <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span>
                <span class="s2">&quot;Grouped inputs currently requires partial compilation to be enabled, this restriction will be relaxed in a future release&quot;</span>
            <span class="p">)</span>

        <span class="n">log</span><span class="p">(</span>
            <span class="n">Level</span><span class="o">.</span><span class="n">Debug</span><span class="p">,</span>
            <span class="s2">&quot;Grouped inputs currently requires additional settings to enable the feature&quot;</span><span class="p">,</span>
        <span class="p">)</span>
        <span class="n">log</span><span class="p">(</span>
            <span class="n">Level</span><span class="o">.</span><span class="n">Debug</span><span class="p">,</span>
            <span class="sd">&quot;&quot;&quot;Adding the following ops to torch_executed_ops:</span>
<span class="sd">    - aten::__getitem__</span>
<span class="sd">    - prim::ListConstruct</span>
<span class="sd">    - prim::ListUnpack</span>
<span class="sd">    - prim::TupleIndex</span>
<span class="sd">    - prim::TupleConstruct</span>
<span class="sd">    - prim::TupleUnpack</span>
<span class="sd">&quot;&quot;&quot;</span><span class="p">,</span>
        <span class="p">)</span>
        <span class="n">compile_spec</span><span class="p">[</span><span class="s2">&quot;torch_fallback&quot;</span><span class="p">][</span><span class="s2">&quot;forced_fallback_ops&quot;</span><span class="p">]</span><span class="o">.</span><span class="n">append</span><span class="p">(</span>
            <span class="s2">&quot;aten::__getitem__&quot;</span>
        <span class="p">)</span>
        <span class="n">compile_spec</span><span class="p">[</span><span class="s2">&quot;torch_fallback&quot;</span><span class="p">][</span><span class="s2">&quot;forced_fallback_ops&quot;</span><span class="p">]</span><span class="o">.</span><span class="n">append</span><span class="p">(</span>
            <span class="s2">&quot;prim::ListConstruct&quot;</span>
        <span class="p">)</span>
        <span class="n">compile_spec</span><span class="p">[</span><span class="s2">&quot;torch_fallback&quot;</span><span class="p">][</span><span class="s2">&quot;forced_fallback_ops&quot;</span><span class="p">]</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="s2">&quot;prim::ListUnpack&quot;</span><span class="p">)</span>
        <span class="n">compile_spec</span><span class="p">[</span><span class="s2">&quot;torch_fallback&quot;</span><span class="p">][</span><span class="s2">&quot;forced_fallback_ops&quot;</span><span class="p">]</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="s2">&quot;prim::TupleIndex&quot;</span><span class="p">)</span>
        <span class="n">compile_spec</span><span class="p">[</span><span class="s2">&quot;torch_fallback&quot;</span><span class="p">][</span><span class="s2">&quot;forced_fallback_ops&quot;</span><span class="p">]</span><span class="o">.</span><span class="n">append</span><span class="p">(</span>
            <span class="s2">&quot;prim::TupleConstruct&quot;</span>
        <span class="p">)</span>
        <span class="n">compile_spec</span><span class="p">[</span><span class="s2">&quot;torch_fallback&quot;</span><span class="p">][</span><span class="s2">&quot;forced_fallback_ops&quot;</span><span class="p">]</span><span class="o">.</span><span class="n">append</span><span class="p">(</span>
            <span class="s2">&quot;prim::TupleUnpack&quot;</span>
        <span class="p">)</span>

    <span class="k">else</span><span class="p">:</span>
        <span class="k">raise</span> <span class="ne">KeyError</span><span class="p">(</span>
            <span class="s1">&#39;Module input definitions are requried to compile module. Provide a list of torch_tensorrt.Input keyed to &quot;inputs&quot; in the compile spec&#39;</span>
        <span class="p">)</span>

    <span class="k">if</span> <span class="s2">&quot;enabled_precisions&quot;</span> <span class="ow">in</span> <span class="n">compile_spec</span><span class="p">:</span>
        <span class="n">info</span><span class="o">.</span><span class="n">enabled_precisions</span> <span class="o">=</span> <span class="n">_parse_enabled_precisions</span><span class="p">(</span>
            <span class="n">compile_spec</span><span class="p">[</span><span class="s2">&quot;enabled_precisions&quot;</span><span class="p">]</span>
        <span class="p">)</span>

    <span class="k">if</span> <span class="s2">&quot;calibrator&quot;</span> <span class="ow">in</span> <span class="n">compile_spec</span><span class="p">:</span>
        <span class="n">info</span><span class="o">.</span><span class="n">ptq_calibrator</span> <span class="o">=</span> <span class="n">compile_spec</span><span class="p">[</span><span class="s2">&quot;calibrator&quot;</span><span class="p">]</span>

    <span class="k">if</span> <span class="s2">&quot;sparse_weights&quot;</span> <span class="ow">in</span> <span class="n">compile_spec</span><span class="p">:</span>
        <span class="k">assert</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">compile_spec</span><span class="p">[</span><span class="s2">&quot;sparse_weights&quot;</span><span class="p">],</span> <span class="nb">bool</span><span class="p">)</span>
        <span class="n">info</span><span class="o">.</span><span class="n">sparse_weights</span> <span class="o">=</span> <span class="n">compile_spec</span><span class="p">[</span><span class="s2">&quot;sparse_weights&quot;</span><span class="p">]</span>

    <span class="k">if</span> <span class="s2">&quot;disable_tf32&quot;</span> <span class="ow">in</span> <span class="n">compile_spec</span><span class="p">:</span>
        <span class="k">assert</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">compile_spec</span><span class="p">[</span><span class="s2">&quot;disable_tf32&quot;</span><span class="p">],</span> <span class="nb">bool</span><span class="p">)</span>
        <span class="n">info</span><span class="o">.</span><span class="n">disable_tf32</span> <span class="o">=</span> <span class="n">compile_spec</span><span class="p">[</span><span class="s2">&quot;disable_tf32&quot;</span><span class="p">]</span>

    <span class="k">if</span> <span class="s2">&quot;refit&quot;</span> <span class="ow">in</span> <span class="n">compile_spec</span><span class="p">:</span>
        <span class="k">assert</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">compile_spec</span><span class="p">[</span><span class="s2">&quot;refit&quot;</span><span class="p">],</span> <span class="nb">bool</span><span class="p">)</span>
        <span class="n">info</span><span class="o">.</span><span class="n">refit</span> <span class="o">=</span> <span class="n">compile_spec</span><span class="p">[</span><span class="s2">&quot;refit&quot;</span><span class="p">]</span>

    <span class="k">if</span> <span class="s2">&quot;debug&quot;</span> <span class="ow">in</span> <span class="n">compile_spec</span><span class="p">:</span>
        <span class="k">assert</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">compile_spec</span><span class="p">[</span><span class="s2">&quot;debug&quot;</span><span class="p">],</span> <span class="nb">bool</span><span class="p">)</span>
        <span class="n">info</span><span class="o">.</span><span class="n">debug</span> <span class="o">=</span> <span class="n">compile_spec</span><span class="p">[</span><span class="s2">&quot;debug&quot;</span><span class="p">]</span>

    <span class="k">if</span> <span class="s2">&quot;device&quot;</span> <span class="ow">in</span> <span class="n">compile_spec</span><span class="p">:</span>
        <span class="n">info</span><span class="o">.</span><span class="n">device</span> <span class="o">=</span> <span class="n">_parse_device</span><span class="p">(</span><span class="n">compile_spec</span><span class="p">[</span><span class="s2">&quot;device&quot;</span><span class="p">])</span>

    <span class="k">if</span> <span class="s2">&quot;capability&quot;</span> <span class="ow">in</span> <span class="n">compile_spec</span><span class="p">:</span>
        <span class="k">assert</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">compile_spec</span><span class="p">[</span><span class="s2">&quot;capability&quot;</span><span class="p">],</span> <span class="n">_enums</span><span class="o">.</span><span class="n">EngineCapability</span><span class="p">)</span>
        <span class="n">info</span><span class="o">.</span><span class="n">capability</span> <span class="o">=</span> <span class="n">compile_spec</span><span class="p">[</span><span class="s2">&quot;capability&quot;</span><span class="p">]</span>

    <span class="k">if</span> <span class="s2">&quot;num_avg_timing_iters&quot;</span> <span class="ow">in</span> <span class="n">compile_spec</span><span class="p">:</span>
        <span class="k">assert</span> <span class="nb">type</span><span class="p">(</span><span class="n">compile_spec</span><span class="p">[</span><span class="s2">&quot;num_avg_timing_iters&quot;</span><span class="p">])</span> <span class="ow">is</span> <span class="nb">int</span>
        <span class="n">info</span><span class="o">.</span><span class="n">num_avg_timing_iters</span> <span class="o">=</span> <span class="n">compile_spec</span><span class="p">[</span><span class="s2">&quot;num_avg_timing_iters&quot;</span><span class="p">]</span>

    <span class="k">if</span> <span class="s2">&quot;workspace_size&quot;</span> <span class="ow">in</span> <span class="n">compile_spec</span><span class="p">:</span>
        <span class="k">assert</span> <span class="nb">type</span><span class="p">(</span><span class="n">compile_spec</span><span class="p">[</span><span class="s2">&quot;workspace_size&quot;</span><span class="p">])</span> <span class="ow">is</span> <span class="nb">int</span>
        <span class="n">info</span><span class="o">.</span><span class="n">workspace_size</span> <span class="o">=</span> <span class="n">compile_spec</span><span class="p">[</span><span class="s2">&quot;workspace_size&quot;</span><span class="p">]</span>

    <span class="k">if</span> <span class="s2">&quot;dla_sram_size&quot;</span> <span class="ow">in</span> <span class="n">compile_spec</span><span class="p">:</span>
        <span class="k">assert</span> <span class="nb">type</span><span class="p">(</span><span class="n">compile_spec</span><span class="p">[</span><span class="s2">&quot;dla_sram_size&quot;</span><span class="p">])</span> <span class="ow">is</span> <span class="nb">int</span>
        <span class="n">info</span><span class="o">.</span><span class="n">dla_sram_size</span> <span class="o">=</span> <span class="n">compile_spec</span><span class="p">[</span><span class="s2">&quot;dla_sram_size&quot;</span><span class="p">]</span>

    <span class="k">if</span> <span class="s2">&quot;dla_local_dram_size&quot;</span> <span class="ow">in</span> <span class="n">compile_spec</span><span class="p">:</span>
        <span class="k">assert</span> <span class="nb">type</span><span class="p">(</span><span class="n">compile_spec</span><span class="p">[</span><span class="s2">&quot;dla_local_dram_size&quot;</span><span class="p">])</span> <span class="ow">is</span> <span class="nb">int</span>
        <span class="n">info</span><span class="o">.</span><span class="n">dla_local_dram_size</span> <span class="o">=</span> <span class="n">compile_spec</span><span class="p">[</span><span class="s2">&quot;dla_local_dram_size&quot;</span><span class="p">]</span>

    <span class="k">if</span> <span class="s2">&quot;dla_global_dram_size&quot;</span> <span class="ow">in</span> <span class="n">compile_spec</span><span class="p">:</span>
        <span class="k">assert</span> <span class="nb">type</span><span class="p">(</span><span class="n">compile_spec</span><span class="p">[</span><span class="s2">&quot;dla_global_dram_size&quot;</span><span class="p">])</span> <span class="ow">is</span> <span class="nb">int</span>
        <span class="n">info</span><span class="o">.</span><span class="n">dla_global_dram_size</span> <span class="o">=</span> <span class="n">compile_spec</span><span class="p">[</span><span class="s2">&quot;dla_global_dram_size&quot;</span><span class="p">]</span>

    <span class="k">if</span> <span class="s2">&quot;truncate_long_and_double&quot;</span> <span class="ow">in</span> <span class="n">compile_spec</span><span class="p">:</span>
        <span class="k">assert</span> <span class="nb">type</span><span class="p">(</span><span class="n">compile_spec</span><span class="p">[</span><span class="s2">&quot;truncate_long_and_double&quot;</span><span class="p">])</span> <span class="ow">is</span> <span class="nb">bool</span>
        <span class="n">info</span><span class="o">.</span><span class="n">truncate_long_and_double</span> <span class="o">=</span> <span class="n">compile_spec</span><span class="p">[</span><span class="s2">&quot;truncate_long_and_double&quot;</span><span class="p">]</span>

    <span class="k">if</span> <span class="s2">&quot;torch_fallback&quot;</span> <span class="ow">in</span> <span class="n">compile_spec</span><span class="p">:</span>
        <span class="n">info</span><span class="o">.</span><span class="n">torch_fallback</span> <span class="o">=</span> <span class="n">_parse_torch_fallback</span><span class="p">(</span><span class="n">compile_spec</span><span class="p">[</span><span class="s2">&quot;torch_fallback&quot;</span><span class="p">])</span>

    <span class="n">log</span><span class="p">(</span><span class="n">Level</span><span class="o">.</span><span class="n">Debug</span><span class="p">,</span> <span class="nb">str</span><span class="p">(</span><span class="n">info</span><span class="p">))</span>

    <span class="k">return</span> <span class="n">info</span>


<div class="viewcode-block" id="TensorRTCompileSpec"><a class="viewcode-back" href="../../../py_api/ts.html#torch_tensorrt.ts.TensorRTCompileSpec">[docs]</a><span class="k">def</span> <span class="nf">TensorRTCompileSpec</span><span class="p">(</span>
    <span class="n">inputs</span><span class="o">=</span><span class="p">[],</span>
    <span class="n">input_signature</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span>
    <span class="n">device</span><span class="o">=</span><span class="n">Device</span><span class="o">.</span><span class="n">_current_device</span><span class="p">(),</span>
    <span class="n">disable_tf32</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span>
    <span class="n">sparse_weights</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span>
    <span class="n">enabled_precisions</span><span class="o">=</span><span class="nb">set</span><span class="p">(),</span>
    <span class="n">refit</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span>
    <span class="n">debug</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span>
    <span class="n">capability</span><span class="o">=</span><span class="n">_enums</span><span class="o">.</span><span class="n">EngineCapability</span><span class="o">.</span><span class="n">default</span><span class="p">,</span>
    <span class="n">num_avg_timing_iters</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span>
    <span class="n">workspace_size</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span>
    <span class="n">dla_sram_size</span><span class="o">=</span><span class="mi">1048576</span><span class="p">,</span>
    <span class="n">dla_local_dram_size</span><span class="o">=</span><span class="mi">1073741824</span><span class="p">,</span>
    <span class="n">dla_global_dram_size</span><span class="o">=</span><span class="mi">536870912</span><span class="p">,</span>
    <span class="n">truncate_long_and_double</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span>
    <span class="n">calibrator</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span>
<span class="p">)</span> <span class="o">-&gt;</span> <span class="n">torch</span><span class="o">.</span><span class="n">classes</span><span class="o">.</span><span class="n">tensorrt</span><span class="o">.</span><span class="n">CompileSpec</span><span class="p">:</span>
    <span class="sd">&quot;&quot;&quot;Utility to create a formated spec dictionary for using the PyTorch TensorRT backend</span>

<span class="sd">    Keyword Args:</span>
<span class="sd">        inputs (List[Union(torch_tensorrt.Input, torch.Tensor)]): **Required** List of specifications of input shape, dtype and memory layout for inputs to the module. This argument is required. Input Sizes can be specified as torch sizes, tuples or lists. dtypes can be specified using</span>
<span class="sd">            torch datatypes or torch_tensorrt datatypes and you can use either torch devices or the torch_tensorrt device type enum</span>
<span class="sd">            to select device type. ::</span>

<span class="sd">                input=[</span>
<span class="sd">                    torch_tensorrt.Input((1, 3, 224, 224)), # Static NCHW input shape for input #1</span>
<span class="sd">                    torch_tensorrt.Input(</span>
<span class="sd">                        min_shape=(1, 224, 224, 3),</span>
<span class="sd">                        opt_shape=(1, 512, 512, 3),</span>
<span class="sd">                        max_shape=(1, 1024, 1024, 3),</span>
<span class="sd">                        dtype=torch.int32</span>
<span class="sd">                        format=torch.channel_last</span>
<span class="sd">                    ), # Dynamic input shape for input #2</span>
<span class="sd">                    torch.randn((1, 3, 224, 244)) # Use an example tensor and let torch_tensorrt infer settings</span>
<span class="sd">                ]</span>

<span class="sd">        device (Union(torch_tensorrt.Device, torch.device, dict)): Target device for TensorRT engines to run on ::</span>

<span class="sd">            device=torch_tensorrt.Device(&quot;dla:1&quot;, allow_gpu_fallback=True)</span>

<span class="sd">        disable_tf32 (bool): Force FP32 layers to use traditional as FP32 format vs the default behavior of rounding the inputs to 10-bit mantissas before multiplying, but accumulates the sum using 23-bit mantissas</span>
<span class="sd">        sparse_weights (bool): Enable sparsity for convolution and fully connected layers.</span>
<span class="sd">        enabled_precision (Set(Union(torch.dtype, torch_tensorrt.dtype))): The set of datatypes that TensorRT can use when selecting kernels</span>
<span class="sd">        refit (bool): Enable refitting</span>
<span class="sd">        debug (bool): Enable debuggable engine</span>
<span class="sd">        capability (torch_tensorrt.EngineCapability): Restrict kernel selection to safe gpu kernels or safe dla kernels</span>
<span class="sd">        num_avg_timing_iters (int): Number of averaging timing iterations used to select kernels</span>
<span class="sd">        workspace_size (int): Maximum size of workspace given to TensorRT</span>
<span class="sd">        truncate_long_and_double (bool): Truncate weights provided in int64 or double (float64) to int32 and float32</span>
<span class="sd">        calibrator (Union(torch_tensorrt._C.IInt8Calibrator, tensorrt.IInt8Calibrator)): Calibrator object which will provide data to the PTQ system for INT8 Calibration</span>

<span class="sd">      Returns:</span>
<span class="sd">        torch.classes.tensorrt.CompileSpec: List of methods and formated spec objects to be provided to ``torch._C._jit_to_tensorrt``</span>
<span class="sd">    &quot;&quot;&quot;</span>

    <span class="n">compile_spec</span> <span class="o">=</span> <span class="p">{</span>
        <span class="s2">&quot;inputs&quot;</span><span class="p">:</span> <span class="n">inputs</span><span class="p">,</span>
        <span class="c1"># &quot;input_signature&quot;: input_signature,</span>
        <span class="s2">&quot;device&quot;</span><span class="p">:</span> <span class="n">device</span><span class="p">,</span>
        <span class="s2">&quot;disable_tf32&quot;</span><span class="p">:</span> <span class="n">disable_tf32</span><span class="p">,</span>  <span class="c1"># Force FP32 layers to use traditional as FP32 format vs the default behavior of rounding the inputs to 10-bit mantissas before multiplying, but accumulates the sum using 23-bit mantissas</span>
        <span class="s2">&quot;sparse_weights&quot;</span><span class="p">:</span> <span class="n">sparse_weights</span><span class="p">,</span>  <span class="c1"># Enable sparsity for convolution and fully connected layers.</span>
        <span class="s2">&quot;enabled_precisions&quot;</span><span class="p">:</span> <span class="n">enabled_precisions</span><span class="p">,</span>  <span class="c1"># Enabling FP16 kernels</span>
        <span class="s2">&quot;refit&quot;</span><span class="p">:</span> <span class="n">refit</span><span class="p">,</span>  <span class="c1"># enable refit</span>
        <span class="s2">&quot;debug&quot;</span><span class="p">:</span> <span class="n">debug</span><span class="p">,</span>  <span class="c1"># enable debuggable engine</span>
        <span class="s2">&quot;capability&quot;</span><span class="p">:</span> <span class="n">capability</span><span class="p">,</span>  <span class="c1"># Restrict kernel selection to safe gpu kernels or safe dla kernels</span>
        <span class="s2">&quot;num_avg_timing_iters&quot;</span><span class="p">:</span> <span class="n">num_avg_timing_iters</span><span class="p">,</span>  <span class="c1"># Number of averaging timing iterations used to select kernels</span>
        <span class="s2">&quot;workspace_size&quot;</span><span class="p">:</span> <span class="n">workspace_size</span><span class="p">,</span>  <span class="c1"># Maximum size of workspace given to TensorRT</span>
        <span class="s2">&quot;dla_sram_size&quot;</span><span class="p">:</span> <span class="n">dla_sram_size</span><span class="p">,</span>  <span class="c1"># Fast software managed RAM used by DLA to communicate within a layer.</span>
        <span class="s2">&quot;dla_local_dram_size&quot;</span><span class="p">:</span> <span class="n">dla_local_dram_size</span><span class="p">,</span>  <span class="c1"># Host RAM used by DLA to share intermediate tensor data across operations</span>
        <span class="s2">&quot;dla_global_dram_size&quot;</span><span class="p">:</span> <span class="n">dla_global_dram_size</span><span class="p">,</span>  <span class="c1"># Host RAM used by DLA to store weights and metadata for execution</span>
        <span class="s2">&quot;calibrator&quot;</span><span class="p">:</span> <span class="n">calibrator</span><span class="p">,</span>
        <span class="s2">&quot;truncate_long_and_double&quot;</span><span class="p">:</span> <span class="n">truncate_long_and_double</span><span class="p">,</span>
    <span class="p">}</span>

    <span class="n">parsed_spec</span> <span class="o">=</span> <span class="n">_parse_compile_spec</span><span class="p">(</span><span class="n">compile_spec</span><span class="p">)</span>

    <span class="n">backend_spec</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">classes</span><span class="o">.</span><span class="n">tensorrt</span><span class="o">.</span><span class="n">CompileSpec</span><span class="p">()</span>

    <span class="k">if</span> <span class="n">input_signature</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
        <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span>
            <span class="s2">&quot;Input signature parsing is not currently supported in the TorchScript backend integration&quot;</span>
        <span class="p">)</span>

    <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">parsed_spec</span><span class="o">.</span><span class="n">inputs</span><span class="p">:</span>
        <span class="n">clone</span> <span class="o">=</span> <span class="n">_internal_input_to_torch_class_input</span><span class="p">(</span><span class="n">i</span><span class="p">)</span>
        <span class="n">backend_spec</span><span class="o">.</span><span class="n">_append_input</span><span class="p">(</span><span class="n">clone</span><span class="p">)</span>

    <span class="n">d</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">classes</span><span class="o">.</span><span class="n">tensorrt</span><span class="o">.</span><span class="n">_Device</span><span class="p">()</span>
    <span class="n">d</span><span class="o">.</span><span class="n">_set_device_type</span><span class="p">(</span><span class="nb">int</span><span class="p">(</span><span class="n">parsed_spec</span><span class="o">.</span><span class="n">device</span><span class="o">.</span><span class="n">device_type</span><span class="p">))</span>
    <span class="n">d</span><span class="o">.</span><span class="n">_set_gpu_id</span><span class="p">(</span><span class="n">parsed_spec</span><span class="o">.</span><span class="n">device</span><span class="o">.</span><span class="n">gpu_id</span><span class="p">)</span>
    <span class="n">d</span><span class="o">.</span><span class="n">_set_dla_core</span><span class="p">(</span><span class="n">parsed_spec</span><span class="o">.</span><span class="n">device</span><span class="o">.</span><span class="n">dla_core</span><span class="p">)</span>
    <span class="n">d</span><span class="o">.</span><span class="n">_set_allow_gpu_fallback</span><span class="p">(</span><span class="n">parsed_spec</span><span class="o">.</span><span class="n">device</span><span class="o">.</span><span class="n">allow_gpu_fallback</span><span class="p">)</span>

    <span class="k">if</span> <span class="n">parsed_spec</span><span class="o">.</span><span class="n">torch_fallback</span><span class="o">.</span><span class="n">enabled</span><span class="p">:</span>
        <span class="k">raise</span> <span class="ne">RuntimeError</span><span class="p">(</span>
            <span class="s2">&quot;Partial module compilation is not currently supported via the PyTorch TensorRT backend. If you need partial compilation, use torch_tensorrt.compile&quot;</span>
        <span class="p">)</span>

    <span class="n">torch_fallback</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">classes</span><span class="o">.</span><span class="n">tensorrt</span><span class="o">.</span><span class="n">_TorchFallback</span><span class="p">()</span>
    <span class="n">torch_fallback</span><span class="o">.</span><span class="n">_set_enabled</span><span class="p">(</span><span class="n">parsed_spec</span><span class="o">.</span><span class="n">torch_fallback</span><span class="o">.</span><span class="n">enabled</span><span class="p">)</span>
    <span class="n">torch_fallback</span><span class="o">.</span><span class="n">_set_min_block_size</span><span class="p">(</span><span class="n">parsed_spec</span><span class="o">.</span><span class="n">torch_fallback</span><span class="o">.</span><span class="n">min_block_size</span><span class="p">)</span>
    <span class="n">torch_fallback</span><span class="o">.</span><span class="n">_set_forced_fallback_operators</span><span class="p">(</span>
        <span class="n">parsed_spec</span><span class="o">.</span><span class="n">torch_fallback</span><span class="o">.</span><span class="n">forced_fallback_operators</span>
    <span class="p">)</span>
    <span class="n">torch_fallback</span><span class="o">.</span><span class="n">_set_forced_fallback_modules</span><span class="p">(</span>
        <span class="n">parsed_spec</span><span class="o">.</span><span class="n">torch_fallback</span><span class="o">.</span><span class="n">forced_fallback_modules</span>
    <span class="p">)</span>

    <span class="n">backend_spec</span><span class="o">.</span><span class="n">_set_device</span><span class="p">(</span><span class="n">d</span><span class="p">)</span>
    <span class="n">backend_spec</span><span class="o">.</span><span class="n">_set_torch_fallback</span><span class="p">(</span><span class="n">torch_fallback</span><span class="p">)</span>
    <span class="n">backend_spec</span><span class="o">.</span><span class="n">_set_precisions</span><span class="p">([</span><span class="nb">int</span><span class="p">(</span><span class="n">i</span><span class="p">)</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">parsed_spec</span><span class="o">.</span><span class="n">enabled_precisions</span><span class="p">])</span>

    <span class="n">backend_spec</span><span class="o">.</span><span class="n">_set_disable_tf32</span><span class="p">(</span><span class="n">parsed_spec</span><span class="o">.</span><span class="n">disable_tf32</span><span class="p">)</span>
    <span class="n">backend_spec</span><span class="o">.</span><span class="n">_set_refit</span><span class="p">(</span><span class="n">parsed_spec</span><span class="o">.</span><span class="n">refit</span><span class="p">)</span>
    <span class="n">backend_spec</span><span class="o">.</span><span class="n">_set_debug</span><span class="p">(</span><span class="n">parsed_spec</span><span class="o">.</span><span class="n">debug</span><span class="p">)</span>
    <span class="n">backend_spec</span><span class="o">.</span><span class="n">_set_refit</span><span class="p">(</span><span class="n">parsed_spec</span><span class="o">.</span><span class="n">refit</span><span class="p">)</span>
    <span class="n">backend_spec</span><span class="o">.</span><span class="n">_set_capability</span><span class="p">(</span><span class="nb">int</span><span class="p">(</span><span class="n">parsed_spec</span><span class="o">.</span><span class="n">capability</span><span class="p">))</span>
    <span class="n">backend_spec</span><span class="o">.</span><span class="n">_set_num_avg_timing_iters</span><span class="p">(</span><span class="n">parsed_spec</span><span class="o">.</span><span class="n">num_avg_timing_iters</span><span class="p">)</span>
    <span class="n">backend_spec</span><span class="o">.</span><span class="n">_set_workspace_size</span><span class="p">(</span><span class="n">parsed_spec</span><span class="o">.</span><span class="n">workspace_size</span><span class="p">)</span>
    <span class="n">backend_spec</span><span class="o">.</span><span class="n">_set_dla_sram_size</span><span class="p">(</span><span class="n">parsed_spec</span><span class="o">.</span><span class="n">dla_sram_size</span><span class="p">)</span>
    <span class="n">backend_spec</span><span class="o">.</span><span class="n">_set_dla_local_dram_size</span><span class="p">(</span><span class="n">parsed_spec</span><span class="o">.</span><span class="n">dla_local_dram_size</span><span class="p">)</span>
    <span class="n">backend_spec</span><span class="o">.</span><span class="n">_set_dla_global_dram_size</span><span class="p">(</span><span class="n">parsed_spec</span><span class="o">.</span><span class="n">dla_global_dram_size</span><span class="p">)</span>
    <span class="n">backend_spec</span><span class="o">.</span><span class="n">_set_truncate_long_and_double</span><span class="p">(</span><span class="n">parsed_spec</span><span class="o">.</span><span class="n">truncate_long_and_double</span><span class="p">)</span>
    <span class="n">backend_spec</span><span class="o">.</span><span class="n">_set_ptq_calibrator</span><span class="p">(</span><span class="n">parsed_spec</span><span class="o">.</span><span class="n">_get_calibrator_handle</span><span class="p">())</span>

    <span class="k">return</span> <span class="n">backend_spec</span></div>
</pre></div>

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